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At least 109 records · Page 6

Magnetospheric space plasma investigations

Topics and investigations covering this period of this semiannual report period (August 1994 - January 1995) are as follows: (1) Generalized SemiKinetic (GSK) modeling of the synergistic interaction of transverse heating of ionospheric ions and magnetospheric plasma-driven electric potentials on the auroral plasma transport. Also, presentations of GSK modeling of auroral electron precipitation effects on ionospheric plasma outflows, of ExB effects on such outflow, and on warm plasma thermalization and other effects during refilling with pre-existing warm plasmas; (2) Referees' reports received on the statistical study of the latitudinal distributions of core plasmas along the L = 4.6 field line using DE-1/RIMS data. Other work is concerned in the same field, field-aligned flows and trapped ion distributions; and (3) A short study has been carried out on heating processes in low density flux tubes in the outer plasmasphere. The purpose was to determine whether the high ion temperatures observed in these flux tubes were due to heat sources operating through the thermal electrons or directly to the ions. Other investigations center along the same area of plasmasphere-ionosphere coupling. The empirical techniques and model, the listing of hardware calibrated, and/or tested, and a description of notable meetings attended is included in this report, along with a list of all present publication in submission or accepted and those reference papers that have resulted from this work thus far.

Comfort, Richard H.

Capacity of Pulse-Position Modulation (PPM) on Gaussian and Webb Channels

This article computes the capacity of various idealized soft-decision channels modeling an optical channel using an avalanche photodiode detector (APD) and pulse-position modulation (PPM). The capacity of this optical channel depends in a complicated way on the physical parameters of the APD and the constraints imposed by the PPM orthogonal signaling set. This article attempts to identify and separate the effects of several fundamental parameters on the capacity of the APD-detected optical PPM channel. First, an overall signal-to-noise ratio (SNR) parameter is de ned such that the capacity as a function of a bit-normalized version of this SNR drops precipitously toward zero at quasi-brick-wall limits on bit SNR that are numerically the same as the well-understood brick-wall limits for the standard additive white Gaussian noise (AWGN) channel. A second parameter is used to quantify the effects on capacity of one unique facet of the optical PPM channel (as compared with the standard AWGN channel) that causes the noise variance to be higher in signal slots than in nonsignal slots. This nonuniform noise variance yields interesting capacity effects even when the channel model is AWGN. A third parameter is used to measure the effects on capacity of the difference between an AWGN model and a non-Gaussian model proposed by Webb (see reference in [2]) for approximating the statistics of the APD-detected optical channel. Finally, a fourth parameter is used to quantify the blending of a Webb model with a pure AWGN model to account for thermal noise. Numerical results show that the capacity of M-ary orthogonal signaling on the Webb channel exhibits the same brick-wall Shannon limit, (M ln 2)=(M 1), as on the AWGN channel ( 1:59 dB for large M). Results also compare the capacity obtained by hard- and soft-output channels and indicate that soft-output channels o er a 3-dB advantage.

Dolinar, S.

Improved Aerothermal Reliability Analysis Enabled by the Mars Sample Return Earth Entry System Aerothermal Database

The Mars Sample Return (MSR) campaign is a series of missions designed to retrieve Martian rock and soil samples for detailed study on Earth. The campaign is split into three primary phases: sample collection with the Mars2020 rover, retrieval with the Sample Return Lander (SRL) and Mars Ascent Vehicle (MAV), and then return to Earth with the Earth Return Orbiter (ERO) and Capture, Containment, and Return System (CCRS) [1]. The final sequence in the Earth return phase is the delivery and entry of the Earth Entry System (EES) sample return capsule. Due to unprecedented planetary protection concerns, the sample return capsule is subject to strict reliability requirements. To this end, the MSR-EES aerothermal team has implemented a flexible aerothermal database architecture capable of integration with state-of-the-art trajectory codes to provide a more rigorous aerothermal reliability analysis. The EES database enables the generation of environments at any location on the heatshield and can incorporate trajectory uncertainties to both statistically quantify aerothermal environments for arcjet testing and produce material response boundary conditions to rigorously select thermal protection system (TPS) sizing environments. This poster will not discuss the fundamental modeling assumptions included in the database, and will instead focus on the downstream reliability analyses that can be performed with a database of this architecture.

MSR-EES

High-Burnup LOCA Burst Susceptibility BISON Analysis in PWRs and BWRs

Accurately assessing high-burnup fuel behavior during loss-of-coolant accidents (LOCAs) is essential for understanding fuel fragmentation, relocation, and dispersal (FFRD) risks across the US light-water reactor fleet. This work updates previous Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program multiphysics LOCA analyses for a pressurized water reactor (PWR) and a boiling water reactor (BWR) by incorporating recent model and material property advancements in the BISON fuel performance code, including a high-burnup structure (HBS) model, revised cladding burst criteria, and updated thermal–mechanical correlations. This update was needed to support ongoing industry initiatives and upcoming regulatory changes. Full-core, rod-resolved operating histories generated using Virtual Environment for Reactor Analysis (VERA) and system-level LOCA conditions obtained from TRACE were applied to statistically representative rod samples in BISON to evaluate burst behavior and FFRD susceptibility. These calculations used two cladding burst correlations and three fuel pulverization models so that the predictions of these models could be compared. The updated PWR simulations show markedly improved numerical stability as the number of crashed simulations decreased by 95% compared to the previous study, and hence higher confidence in results. The updated PWR simulations predicted cladding bursts exclusively among once-burned, high-power rods, with two different cladding burst models identifying the same burst-susceptible population. Resulting FFRD susceptibility estimates are significantly reduced compared with earlier studies, driven by cooler predicted fuel and plenum temperatures, lower hoop strains, and reduced fission gas release in the updated models. In contrast, none of the BWR rods were predicted to burst under either burst criterion, reaffirming minimal BWR FFRD susceptibility even with updated HBS and material models. Comparisons between the PWR and BWR end-of-cycle predictions are made. Comparison with prior work highlights significant shifts in PWR fuel performance metrics and confirmation of earlier BWR conclusions. Overall, the updated results underscore the importance of having high-resolution detailed modeling capability and continuously integrating evolving material models and physics into high-resolution multiphysics simulations. The unified assessment presented here strengthens confidence in predicting high-burnup LOCA behavior by improving agreement between different cladding burst correlations. These results also provide an improved foundation for future BISON model development, FFRD susceptibility calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Computational Material Processing in Microgravity

Working with Professor David Matthiesen at Case Western Reserve University (CWRU) a computer model of the DPIMS (Diffusion Processes in Molten Semiconductors) space experiment was developed that is able to predict the thermal field, flow field and concentration profile within a molten germanium capillary under both ground-based and microgravity conditions as illustrated. These models are coupled with a novel nonlinear statistical methodology for estimating the diffusion coefficient from measured concentration values after a given time that yields a more accurate estimate than traditional methods. This code was integrated into a web-based application that has become a standard tool used by engineers in the Materials Science Department at CWRU.

Source record

Associated with aerospace vehicles development of methodologies for the estimation of thermal properties

Thermal stress analyses are an important aspect in the development of aerospace vehicles at NASA-LaRC. These analyses require knowledge of the temperature distributions within the vehicle structures which consequently necessitates the need for accurate thermal property data. The overall goal of this ongoing research effort is to develop methodologies for the estimation of the thermal property data needed to describe the temperature responses of these complex structures. The research strategy undertaken utilizes a building block approach. The idea here is to first focus on the development of property estimation methodologies for relatively simple conditions, such as isotropic materials at constant temperatures, and then systematically modify the technique for the analysis of more and more complex systems, such as anisotropic multi-component systems. The estimation methodology utilized is a statistically based method which incorporates experimental data and a mathematical model of the system. Several aspects of this overall research effort were investigated during the time of the ASEE summer program. One important aspect involved the calibration of the estimation procedure for the estimation of the thermal properties through the thickness of a standard material. Transient experiments were conducted using a Pyrex standard at various temperatures, and then the thermal properties (thermal conductivity and volumetric heat capacity) were estimated at each temperature. Confidence regions for the estimated values were also determined. These results were then compared to documented values. Another set of experimental tests were conducted on carbon composite samples at different temperatures. Again, the thermal properties were estimated for each temperature, and the results were compared with values obtained using another technique. In both sets of experiments, a 10-15 percent off-set between the estimated values and the previously determined values was found. Another effort was related to the development of the experimental techniques. Initial experiments required a resistance heater placed between two samples. The design was modified such that the heater was placed on the surface of only one sample, as would be necessary in the analysis of built up structures. Experiments using the modified technique were conducted on the composite sample used previously at different temperatures. The results were within 5 percent of those found using two samples. Finally, an initial heat transfer analysis, including conduction, convection and radiation components, was completed on a titanium sandwich structural sample. Experiments utilizing this sample are currently being designed and will be used to first estimate the material's effective thermal conductivity and later to determine the properties associated with each individual heat transfer component.

Scott, Elaine P.

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing

The definition and specification of the near earth environmental criteria for spacecraft thermal design

The variation of the earth's thermal and albedo radiation received by a near-earth orbiting space vehicle or space payload as a result of temporal variation of the earth atmosphere is discussed. A statistical study of current satellite data for determining probability distributions is proposed. With these distributions the thermal designer can define confidence levels on predicted temperature ranges which are compatible with engineering models for use in design, failure probabilities, and spacecraft cost estimates. Use of the distributions in environmental criteria guidelines is also considered.

Gary, G. A.

Statistical properties of the interplanetary microscale fluctuations

Results are reported for a statistical study of short-period fluctuations in the interplanetary plasma velocity and magnetic field. The data base used consists of measurements of the interplanetary plasma and magnetic field by Pioneer 6 with a time resolution of 72 sec and by Mariner 5 with a resolution of 5 min. The analysis is conducted to characterize the parent population from which all individual microscale events on these time scales are drawn. The microscale changes are grouped according to their energy densities relative to the energy density of the background magnetic field, and it is found that each grouping exhibits certain statistical properties within the limits of observational uncertainty. It is noted that these statistical properties are purely observational and independent of any physical model which may be used to interpret them. The results are discussed in the context of MHD discontinuity theory for a thermally anisotropic plasma.

Belcher, J. W.

NASA Tech Briefs, May 2007

Topics include: Noise-Canceling Helmet Audio System; Program Analyzes Spacecraft/Ground Radio Links; Two-Way Communication Using RFID Equipment and Techniques; Six-Message Electromechanical Display System; Scanning Terahertz Heterodyne Imaging Systems; Master Clock and Time-Signal-Distribution System; Synchronous Phase-Resolving Flash Range Imaging; Integrated Radial Probe Transition From MMIC to Waveguide; Bar-Code System for a Microbiological Laboratory; MMIC Amplifier Produces Gain of 10 dB at 235 GHz; Mapping Nearby Terrain in 3D by Use of a Grid of Laser Spots; Digital Beam Deflectors Based Partly on Liquid Crystals; Narrow-Band WGM Optical Filters With Tunable FSRs; Better Finite-Element Analysis of Composite Shell Structures; Computing Spacecraft-Pointing Vectors for Limb Tracking; Enhanced Master Controller Unit Tester; Rover Graphical Simulator; Increasing Durability of Flame-Sprayed Strain Gauges; Multifunctional, High-Temperature Nanocomposites; Multilayer Impregnated Fibrous Thermal Insulation Tiles; Radiation-Shielding Polymer/Soil Composites; Film/Adhesive Processing Module for Fiber-Placement Processing of Composites; Fabrication of Submillimeter Axisymmetric Optical Components; Electrochemical Disposal of Hydrazines in Water; Statistical Model of Evaporating Multicomponent Fuel Drops; Resistively Heated SiC Nozzle for Generating Molecular Beams; Compact Packaging of Photonic Millimeter-Wave Receiver; Diffractive Combiner of Single-Mode Pump Laser-Diode Beams; Wide-Band, High-Quantum-Efficiency Photodetector; A Robustly Stabilizing Model Predictive Control Algorithm; Modeling Evaporation of Drops of Different Kerosenes; Development of Vapor-Phase Catalytic Ammonia Removal System; Several Developments in Space Tethers; Design Concept for a Nuclear Reactor-Powered Mars Rover; Formation-Initialization Algorithm for N Spacecraft; and DNSs of Multicomponent Gaseous and Drop-Laden Mixing Layers Achieving Transition to Turbulence.

Source record

Thermal scale modeling

Complex system study data indicate that factors associated with multilayer insulation pose major problem in scale modeling, that numerical analysis aids correction for known compromises of scaling criteria, and that probable errors in scale modeling experiments fall within range predicted by statistical analysis.

Mac Gregor, R. K.

Recent thermal models of the chromosphere

The paper describes recent research on the calculation of solar chromospheric models. The models included here are based on the observed spectrum, and on the assumption of hydrostatic equilibrium. The calculations depend on realistic solutions of the radiative transfer and statistical equilibrium equations for optically thick lines and continua, and on including the effects of large numbers of lines throughout the spectrum. Although spectroheliograms show that the structure of the chromosphere is highly complex, one-dimensional models of particular features are reasonably successful in matching observed spectra. There has been considerable recent progress in applying such models to the interpretation of chromospheric observations.

Avrett, E. H.

An Analytic Function of Lunar Surface Temperature for Exospheric Modeling

We present an analytic expression to represent the lunar surface temperature as a function of Sun-state latitude and local time. The approximation represents neither topographical features nor compositional effects and therefore does not change as a function of selenographic latitude and longitude. The function reproduces the surface temperature measured by Diviner to within +/-10 K at 72% of grid points for dayside solar zenith angles of less than 80, and at 98% of grid points for nightside solar zenith angles greater than 100. The analytic function is least accurate at the terminator, where there is a strong gradient in the temperature, and the polar regions. Topographic features have a larger effect on the actual temperature near the terminator than at other solar zenith angles. For exospheric modeling the effects of topography on the thermal model can be approximated by using an effective longitude for determining the temperature. This effective longitude is randomly redistributed with 1 sigma of 4.5deg. The resulting ''roughened'' analytical model well represents the statistical dispersion in the Diviner data and is expected to be generally useful for future models of lunar surface temperature, especially those implemented within exospheric simulations that address questions of volatile transport.

moon

A Survey of Eight Hot Jupiters in Secondary Eclipse Using WIRCam at CFHT

We present near-infrared high-precision photometry for eight transiting hot Jupiters observed during their predicted secondary eclipses. Our observations were carried out using the staring mode of the WIRCam instrument on the Canada-France-Hawaii Telescope (CFHT).We present the observing strategies and data reduction methods which delivered time series photometry with statistical photometric precision as low as 0.11 percent. We performed a Bayesian analysis to model the eclipse parameters and systematics simultaneously. The measured planet-to-star flux ratios allowed us to constrain the thermal emission from the day side of these hot Jupiters, as we derived the planet brightness temperatures. Our results combined with previously observed eclipses reveal an excess in the brightness temperatures relative to the blackbody prediction for the equilibrium temperatures of the planets for a wide range of heat redistribution factors. We find a trend that this excess appears to be larger for planets with lower equilibrium temperatures. This may imply some additional sources of radiation, such as reflected light from the host star and/or thermal emission from residual internal heat from the formation of the planet.

Bayesian Analysis

Measurement uncertainty and feasibility study of a flush airdata system for a hypersonic flight experiment

Presented is a feasibility and error analysis for a hypersonic flush airdata system on a hypersonic flight experiment (HYFLITE). HYFLITE heating loads make intrusive airdata measurement impractical. Although this analysis is specifically for the HYFLITE vehicle and trajectory, the problems analyzed are generally applicable to hypersonic vehicles. A layout of the flush-port matrix is shown. Surface pressures are related airdata parameters using a simple aerodynamic model. The model is linearized using small perturbations and inverted using nonlinear least-squares. Effects of various error sources on the overall uncertainty are evaluated using an error simulation. Error sources modeled include boundarylayer/viscous interactions, pneumatic lag, thermal transpiration in the sensor pressure tubing, misalignment in the matrix layout, thermal warping of the vehicle nose, sampling resolution, and transducer error. Using simulated pressure data for input to the estimation algorithm, effects caused by various error sources are analyzed by comparing estimator outputs with the original trajectory. To obtain ensemble averages the simulation is run repeatedly and output statistics are compiled. Output errors resulting from the various error sources are presented as a function of Mach number. Final uncertainties with all modeled error sources included are presented as a function of Mach number.

Whitmore, Stephen A.

Materials property definition and generation for carbon-carbon and carbon phenolic materials

A data base program to generate statistically significant material-property data for carbon-carbon and carbon phenolic materials to be used in designs of Space Shuttle is described. The program, which will provide data necessary for thermal and stress modeling of Shuttle nozzle and exit cone structures, includes evaluation of tension, compression, shear strength, shear modulus, thermal expansion, thermal conductivity, permeability, and emittance for both materials; the testing of carbon phenolic materials also includes CTE, off-gassing, pyrolysis, and RTG. Materials to be tested will be excised from Space Shuttle inlet, throat, and exit cone billets and modified involute carbon-carbon exit cones; coprocessed blocks, panels, and cylinders will also be tested.

Canfield, A. R.

Stochastic fracture generation and thermo-hydro-mechanical modeling in an equivalent continuum framework for enhanced geothermal systems

Enhanced geothermal systems (EGS) involve fracturing low permeability material to establish well connectivity and then injecting and circulating fluid into the fractured subsurface for geothermal power production. Changes in fracture aperture from contraction of the cooling matrix rock may alter network connectivity and risk thermal short-circuiting. Thermo-hydro-mechanical (THM) models are a useful tool to study these processes. However, as fracture networks are complex, and data may be limited, fracture networks in THM models are often stochastically generated. Given reliance on stochastic fracture networks and THM modeling to represent the subsurface and assess productivity of EGS, increased understanding of the influence of such statistically derived fracture networks on flow and heat transport in THM models is needed. Here, a new fracture process model is developed in the reactive transport code PFLOTRAN to stochastically generate fracture families and simulate changes in fracture aperture over time due to temperature changes of the rock matrix. Sixty-four different fracture networks ranging from well to poorly-connected, are modeled in PFLOTRAN with and without mechanical processes (THM vs TH). Results indicate that for well-connected fracture networks, thermal short-circuiting is less of a concern due to the abundance of available alternative flowpaths. For poorly-connected fracture networks, inclusion of mechanical processes showed steep thermal drawdown coincident with increase in fracture aperture along developing colder flowpaths, demonstrating the risk of thermal short-circuiting. Simulations with additional, larger fractures engineered to establish connectivity in a poorly-fractured subsurface, indicate that while stochastic variation of fracture orientation of the background network had limited influence, such variation in the engineered fractures significantly affected flow and heat transport.

Discrete fracture networks (DFN)

Derivation of Failure Rates and Probability of Failures for the International Space Station Probabilistic Risk Assessment Study

National Aeronautics and Space Administration s (NASA) International Space Station (ISS) Program uses Probabilistic Risk Assessment (PRA) as part of its Continuous Risk Management Process. It is used as a decision and management support tool to not only quantify risk for specific conditions, but more importantly comparing different operational and management options to determine the lowest risk option and provide rationale for management decisions. This paper presents the derivation of the probability distributions used to quantify the failure rates and the probability of failures of the basic events employed in the PRA model of the ISS. The paper will show how a Bayesian approach was used with different sources of data including the actual ISS on orbit failures to enhance the confidence in results of the PRA. As time progresses and more meaningful data is gathered from on orbit failures, an increasingly accurate failure rate probability distribution for the basic events of the ISS PRA model can be obtained. The ISS PRA has been developed by mapping the ISS critical systems such as propulsion, thermal control, or power generation into event sequences diagrams and fault trees. The lowest level of indenture of the fault trees was the orbital replacement units (ORU). The ORU level was chosen consistently with the level of statistically meaningful data that could be obtained from the aerospace industry and from the experts in the field. For example, data was gathered for the solenoid valves present in the propulsion system of the ISS. However valves themselves are composed of parts and the individual failure of these parts was not accounted for in the PRA model. In other words the failure of a spring within a valve was considered a failure of the valve itself.

Vitali, Roberto